For a software system to support the data needs of two or more vertical industries, it usually must make compromises in what data is available, or provide a large superset (e.g. the ability to encompass the data needs of all the industries it is desired to support) with many unused data items in order to satisfy the greatest common denominator. For instance, those demographic data items that may be important in a medical record registration application, may not have any use to a hotels central reservation system.
One way to support multiple vertical markets with the same application or software system (product) is to have a very generic data storage capability which does not have anything specific to a given industry, application or format. The problem with this approach is that the data items which are specific to an industry or application may be those that are most valuable to the customer. Some industries have Electronic Data Interchange Standards that can be used, but they do not fit every application and rarely have wide acceptance.
Another solution to the above problem is to create a large, all encompassing data model which tries to anticipate every conceivable contingency. This is cumbersome to install, and requires that the users wade through unused scaffolding if their particular business does not require the extra fields. And despite best efforts, they may still have requirements which are not included in the model.